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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2016/2017

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DRPS : Course Catalogue : School of Mathematics : Mathematics

Postgraduate Course: MIGSAA Statistics 1 (MATH12019)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 12 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits15 ECTS Credits7.5
Summary*Only students of the MIGSAA CDT may take this course*
One aim is to introduce some key topics which lie at the heart of research in statistical methods and form a basis for more advanced and sophisticated ideas. Another is to develop good computational skills using R, the statistical computing package which is in widespread use for statistical work in academia and industry.
Course description - Introduction to R
- Review of linear models
- Likelihood methods (and optimisation)
- Review of generalised linear models
- Simulation and bootstrapping
- Case study
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2016/17, Not available to visiting students (SS1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 150 ( Lecture Hours 20, Programme Level Learning and Teaching Hours 3, Directed Learning and Independent Learning Hours 127 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Coursework : 100%
Feedback Not entered
No Exam Information
Learning Outcomes
To give students an introductory understanding of some key topics which lie at the heart of research in statistical methods and form a basis for more advanced and sophisticated ideas
Reading List
None
Additional Information
Graduate Attributes and Skills Not entered
Keywordsmigsaa,statistics
Contacts
Course organiserProf A Carbery
Tel: (0131 6)50 5993
Email: A.Carbery@ed.ac.uk
Course secretaryMs Isabelle Hanlon
Tel: (0131 6)50 5955
Email: i.hanlon@ed.ac.uk
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